Macroblock Classification Method for Computation Control Video Coding and Other Video Applications Involving Motions
Weiyao Lin, Bing Zhou, Dong Jiang, Chongyang Zhang · 2013
This chapter proposes a more accurate macroblock (MB) Importance Measure method by classifying macroblocks into different classes. Normally, in a power-rich condition, a high-quality complexity-scalable video coding research (CSVC) strategy is preferred in spite of higher power consumption. The target of the CSVC is to find an efficient way to allocate the available computation budget for different video parts and different coding modules so that the resulting video quality is kept as high as possible under the given computation budget. The detection of motion discontinuity can be very useful in video content analysis or video coding performance improvement. Global motion estimation is another useful application of our class information. Since a video frame may often contain various objects with different motion patterns and directions, motion segmentation is needed to filter out these motion regions before estimating the global motion parameters of the background.